1. Field
Embodiments disclosed herein relate to an image processing technology, and more particularly, to an apparatus and method for parsing a human body image.
2. Description of the Related Art
Recently, active research is being conducted on parsing of a human body image and a wide range of applications to which parsing of a human body image may be applied, for example, human-machine interaction, medical applications, and the like.
Generally, parsing of a human body image is based on matching, classification, and feature analysis.
The matching-based parsing collects a plurality of samples including human body parts, and matches a depth image or a depth-of-field image to a database. Here, the parsing accuracy depends on data in the database.
The classification (categorization)-based parsing involves training a classifier in advance. To train the classifier, a great amount of random training data is required, and parsing accuracy relies on the selection of training data.
The feature analysis-based parsing includes feature extraction and analysis. The need for training data and a database is absent. However, since the extracted feature is sensitive to noise, parsing a human body image having a complicated pose is difficult.
Accordingly, there is a demand for parsing of a human body image with improved accuracy and stability.